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With an extensive 13-year career in the world of data analytics and data science, I am an accomplished Lead Data Scientist currently spearheading initiatives at Amazon. My career is marked by a deep and persistent dedication to leveraging data to derive actionable insights and build data-driven solutions. After obtaining a …

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I've spent a good chunk of my career mentoring folks through various stages of their professional journeys. It's been a rewarding ride, helping many individuals land great jobs and ace interviews, while also supporting others in making career shifts, revamping portfolios, and successfully completing Machine Learning and Deep Learning projects …

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Hello! I'm Venky, and I’m thrilled to share a bit about my journey and how it shapes my approach as a mentor. Currently, I lead a team of applied research scientists and machine learning engineers at Amazon AI in Sunnyvale, California. My work focuses on developing advanced deep learning and …

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Sunny Zhu refers to herself as the bridge between people and data and as a “statistics geek”. She has been engaged in a broad range of analytical works across diversified industries to empower companies to turn data insights into solid business decisions. Working for a decade in data analytics, she …

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I have over 20 years of software development experience, scaling teams from 0 - 30 members. I have had leadership experience at Amazon, Disney, and at various startups. I can coach you on career development, resume reviews, tech interview prep (I have > 2k interviews over my career, and over …

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👋 Ahoy there! I am a Principal Designer with 14+ years of UX work experience (whether as a Designer, a User Researcher and as a Design Consultant). I'm super passionate for great Design and love-love-love helping people whether it's "breaking into tech", acing interviews, and planning careers paths. My mentees …

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Hey there! I'm Shaksham, a seasoned Data Science Mentor specializing in NLP and ML. With over 5 years of experience, I'm passionate about guiding aspiring data enthusiasts towards their goals. Whether you're a beginner or an experienced practitioner, my personalized mentoring approach caters to your needs. Together, we'll unravel complex …

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Eugene is a faith-centric technologist, a serial entrepreneur, angel investor, advisor and mentor. He is founder of REACTIVE LIONS INC. where he is implementing his vision of faith-driven entrepreneurship in the tech world. He is currently running a team of over 40 talented engineers across the US. Eugene is the …

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Discover more Machine Learning trainers

Best books to build Machine Learning understanding.

A well-written and thorough book can be an amazing path to build deeper understanding and also act as a handbook as you discover the internet's vast resources.

These are our and our expert's top picks to get started building relevant skills to widen your career options.

Introduction to Statistical learning

Introduction to Statistical learning

ISL is a fundamental book and popular amongst undergrad and grad students for its clarity and simplicity with explaining concepts. The math required to understand the book is kept to a minimum, making it unique in its format.

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

Bishop's book on pattern recognition is a classic textbook and staple in Machine Learning. Beimg aimed at grad students, but also at researchers and practitioners, it's no easy lecture, but a truly fundamental course book.

Hands-on Machine Learning with Scikit-Learn, Keras and Tensorflow

Hands-on Machine Learning with Scikit-Learn, Keras and Tensorflow

The hands-on Machine Learning book is an amazing piece by Aurélien Géron, taking you from the basics of Machine Learning to applying them to real-word scenarios all in one book.

Federated Learning (Synthesis Lectures)

Federated Learning (Synthesis Lectures)

How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security.

Reinforcement Learning: An Introduction

Reinforcement Learning: An Introduction

Richard Sutton's book on Machine Learning is universally regarded as one of the most fundamental and important pieces on the matter. Reinforcement Learning is quickly becoming a major part of AI innovation, and a good read for any engineer and scientists to go through.

Generative Deep Learning

Generative Deep Learning

It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples o

Pragmatic Programmer

Pragmatic Programmer

At least today, code is our door to building algorithms and complex Machine Learning systems. If you want to invest in becoming a more proficient Machine Learning professional faster, investing in code skills is the way to do so.

Probabilistic Machine Learning: Advanced Topics

Probabilistic Machine Learning: Advanced Topics

An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference.

Mastering Machine Learning on AWS

Mastering Machine Learning on AWS

AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.

Advanced Machine Learning with Python

Advanced Machine Learning with Python

Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.

Courses to deepen your Machine Learning skills.

These days, online courses are no longer just a sequence of videos. They are usually accompanied by projects and a learning community, career advice, keeping you accountable and on the path.

Our experts recommend these courses, from free selections to paid programs.

Udacity's Machine Learning Nanodegree

Udacity's Machine Learning Nanodegree

Udacity has been a pioneer of Machine Learning courses since launching their wide range of ML, Data Science and Robotics courses a few years back. These Nanodegrees are pricey but often come with career support and human project grading.

Fast.ai

Fast.ai

With the motto "making neural nets uncool again", fast.ai is a straight-to-the-point practical (and free!) course that is valued by Machine Learning enthusiasts and engineers worldwide. Fast.ai comes with a community, many practical projects and great content.

Machine Learning A-Z™

Machine Learning A-Z™

Kirill Eremenko's course on Udemy is a classic with almost a million (!) students worldwide. A-Z takes you from a bit of coding knowledge to making your own predictions and building ML models pretty swiftly. At prices between $10 - $20 it's also cheaper than many alternatives.

Deep Learning Specialization

Deep Learning Specialization

In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. 38% of students started a new career after completing this specialization.

MIT Open: Linear Algebra

MIT Open: Linear Algebra

Math is the foundation of Machine Learning and much needed if you need to work on the inner logic of its systems. Senior engineers are encouraged to propose and submit their own papers – and getting your LinAlg back in order is a must for that.

Lex Fridman's MIT Deep Learning

Lex Fridman's MIT Deep Learning

Lex Fridman is the instructor of an immensely popular and fundamental Deep Learning course at MIT. Together with the other MIT AI courses, this can help polish your skills and get the foundations right.

Why you should book a Machine Learning training on MentorCruise

MentorCruise is a career mentorship platform that offers a risk-free trial with each training. We believe that you should be able to test the waters and build confidence before committing to a long-term relationship.

Learn about leading Machine Learning methodologies
Expand your horizon and learn more about the Machine Learning landscape from an expert trainer that has been in your shoes before.
Level up your Machine Learning understanding
Machine Learning is a powerful tool in your arsenal, but it's easy to fall behind the pack. Study advanced topics and stay accountable through a dedicated Machine Learning training.
Speed up your progress
It's not easy to self-teach through online classes. Get the help you need to speed up your Machine Learning progress and reach your goals faster.

Unleash your potential

There’s no match to having a trusted go-to source for addressing your career-specific needs. MentorCruise comes in to give you access to industry-veterans who have been in your place and know exactly what you need.

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